Powering Ocean Giants: The Energetics of Shark and Ray Megafauna

被引：40

作者：

Lawson, Christopher L. ^{[1
]}

Halsey, Lewis G. ^{[2
]}

Hays, Graeme C. ^{[3
]}

Dudgeon, Christine L. ^{[1
]}

Payne, Nicholas L. ^{[4
]}

Bennett, Michael B. ^{[1
]}

White, Craig R. ^{[5
]}

Richardson, Anthony J. ^{[6
,7
]}

机构：

[1] Univ Queensland, Sch Biomed Sci, St Lucia, Qld, Australia

[2] Univ Roehampton, Dept Life Sci, Ctr Res Ecol Evolut & Behav, London, England

[3] Deakin Univ, Ctr Integrat Ecol, Geelong, Vic, Australia

[4] Trinity Coll Dublin, Sch Nat Sci, Dublin, Ireland

[5] Monash Univ, Sch Biol Sci, Ctr Geometr Biol, Melbourne, Vic, Australia

[6] Commonwealth Sci & Ind Res Org CSIRO Oceans & Atm, QBP, St Lucia, Qld, Australia

[7] Univ Queensland, Sch Math & Phys, Ctr Applicat Nat Resource Math, St Lucia, Qld, Australia

来源：

TRENDS IN ECOLOGY & EVOLUTION | 2019年 / 34卷 / 11期

关键词：

METABOLIC-RATE; BODY-MASS; TEMPERATURE; RATES; ACCELERATION; ZOOPLANKTON; REVEALS; ENERGY; LIFE; SIZE;

D O I：

10.1016/j.tree.2019.07.001

中图分类号：

Q14 [生态学（生物生态学）];

学科分类号：

071012 ; 0713 ;

摘要：

Shark and ray megafauna have crucial roles as top predators in many marine ecosystems, but are currently among the most threatened vertebrates and, based on historical extinctions, may be highly susceptible to future environmental perturbations. However, our understanding of their energetics lags behind that of other taxa. Such knowledge is required to answer important ecological questions and predict their responses to ocean warming, which may be limited by ex panding ocean deoxygenation and declining prey availability. To develop bioenergetics models for shark and ray megafauna, incremental improvements in respirometry systems are useful but unlikely to accommodate the largest species. Advances in biologging tools and modelling coulc help answer the most pressing ecological questions about these iconic species.

引用

页码：1009 / 1021

页数：13

共 100 条

[1]

Acevedo-Gutiérrez A, 2002, J EXP BIOL, V205, P1747

[2] Temperature and the vertical movements of oceanic whitetip sharks, Carcharhinus longimanus [J].

Andrzejaczek, Samantha ;

Gleiss, Adrian C. ;

Jordan, Lance K. B. ;

Pattiaratchi, Charitha B. ;

Howey, Lucy A. ;

Brooks, Edward J. ;

Meekan, Mark G. .

SCIENTIFIC REPORTS, 2018, 8

[3] Ecotourism increases the field metabolic rate of whitetip reef sharks [J].

Barnett, Adam ;

Payne, Nicholas L. ;

Semmens, Jayson M. ;

Fitzpatrick, Richard .

BIOLOGICAL CONSERVATION, 2016, 199 :132-136

[4] Ecological impact of the end-Cretaceous extinction on lamniform sharks [J].

Belben, Rachel A. ;

Underwood, Charlie J. ;

Johanson, Zerina ;

Twitchett, Richard J. .

PLOS ONE, 2017, 12 (06)

[5]

Bernal D., 2015, Fish Physiology, V34, P311, DOI DOI 10.1016/B978-0-12-801289-5.00008-0

[6] In situ swimming behaviors and oxygen consumption rates of juvenile lemon sharks (Negaprion brevirostris) [J].

Bouyoucos, Ian A. ;

Suski, Cory D. ;

Mandelman, John W. ;

Brooks, Edward J. .

ENVIRONMENTAL BIOLOGY OF FISHES, 2018, 101 (05) :761-773

[7] Swimming speeds and metabolic rates of semi-captive juvenile lemon sharks (Negaprion brevirostris, Poey) estimated with acceleration biologgers [J].

Bouyoucos, Ian A. ;

Montgomery, Daniel W. ;

Brownscombe, Jacob W. ;

Cooke, Steven J. ;

Suski, Cory D. ;

Mandelman, John W. ;

Brooks, Edward J. .

JOURNAL OF EXPERIMENTAL MARINE BIOLOGY AND ECOLOGY, 2017, 486 :245-254

[8] Optimal migration energetics of humpback whales and the implications of disturbance [J].

Braithwaite, Janelle E. ;

Meeuwig, Jessica J. ;

Hipsey, Matthew R. .

CONSERVATION PHYSIOLOGY, 2015, 3

[9] Declining oxygen in the global ocean and coastal waters [J].

Breitburg, Denise ;

Levin, Lisa A. ;

Oschlies, Andreas ;

Gregoire, Marilaure ;

Chavez, Francisco P. ;

Conley, Daniel J. ;

Garcon, Veronique ;

Gilbert, Denis ;

Gutierrez, Dimitri ;

Isensee, Kirsten ;

Jacinto, Gil S. ;

Limburg, Karin E. ;

Montes, Ivonne ;

Naqvi, S. W. A. ;

Pitcher, Grant C. ;

Rabalais, Nancy N. ;

Roman, Michael R. ;

Rose, Kenneth A. ;

Seibel, Brad A. ;

Telszewski, Maciej ;

Yasuhara, Moriaki ;

Zhang, Jing .

SCIENCE, 2018, 359 (6371) :46-+

[10] Development and application of a machine learning algorithm for classification of elasmobranch behaviour from accelerometry data [J].

Brewster, L. R. ;

Dale, J. J. ;

Guttridge, T. L. ;

Gruber, S. H. ;

Hansell, A. C. ;

Elliott, M. ;

Cowx, I. G. ;

Whitney, N. M. ;

Gleiss, A. C. .

MARINE BIOLOGY, 2018, 165 (04)

← 1 2 3 4 5 6 7 8 9 10 →